Statistical signal processing for detection of buried landmines using quadrupole resonance
Quadrupole resonance (QR) is a technique that discriminates mines from clutter by exploiting unique properties of explosives. However, explosives detection via QR is complicated by several issues. This article discusses several signal processing tools developed to further enhance the utility of QR explosives (mine) detection. In particular, with regard to the uncertainties concerning the background environment and sensor height, statistical signal processing strategies are explored to rigorously account for the inherent variability in these parameters.